Virginia Smith is an assistant professor in the Machine Learning Department at Carnegie Mellon University. Her research spans machine learning, optimization, and distributed systems. Virginia’s work addresses challenges related to optimization, privacy, fairness, and robustness in distributed settings in order to make federated and on-device learning safe, efficient, and reliable. Her work has been recognized by numerous awards, including an MIT TR35 Innovator Award, Facebook Faculty Award, and Google Research Awards. Prior to CMU, Virginia was a postdoc at Stanford University and received a Ph.D. in Computer Science from UC Berkeley.